Over the past two decades, significant advances have been made in speech analysis and speech pattern recognition techniques, however, the penetration of these advances into the speech disorders research arena has lagged, and penetration into the clinic is virtually non-existent. We propose to address this lag by adapting and extending speech recognition technology based on Hidden Markov Modeling (HMM) to an analysis of speech from children with speech delay of unknown origin. We will demonstrate the efficacy of this approach by (a) establishing the effectiveness of the proposed analysis techniques in identifying acoustically defined categories of segmental distortions (endophenotypes), (b) examining these acoustically-defined endophenotypes for evidence of heritability and (c) searching for evidence of genetic linkage of the obtained endophenotypes to a region of chromosome 3 that has been implicated in speech disorders. That is, three aims will be addressed: Aim 1: Extension and validation of a new HMM-based approach to the identification and classification of children who are diagnosed with developmental phonological delays. We will develop a new database of information associated with 75 five to nine year old sibling pairs, at least one of whom is diagnosed with SD. Acoustic speech data and perceptual data will provide feature sets in the database for use in identifying possible endophenotypes. Aim 2: Examination of familiarity of acoustic and perceptual measures in developmental phonological disorders to determine whether these measures define heritable quantitative traits. We will assess heritability of the acoustic and perceptual variables as compared with more classically defined speech variables using cluster and sibling correlation analysis to determine whether the more refined phenotypes are more/less heritable that those typically used in speech genetics studies. We hypothesize that the acoustic phenotypes will define a heritable quantitative trait that can be used for future genome screening studies to identify genes involved in speech. Aim 3: Assessment of linkage to chromosome 3 in speech-disordered sibling pairs. Recent studies have shown evidence for linkage of SD to the pericentromeric region of chromosome 3 (Stein et al., 2004). We will use quantitative trait linkage analyses for the speech, acoustic and perceptual phenotypes to determine whether there is evidence for linkage to this region in this patient cohort.